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海外のトップ頭脳も予測した！　最新テクノロジーによる2030年の世界　テクノロジーはどこまで進化するのか？人間は駆逐される？AIって結局、わたしたちにどんな影響を与えるの？

ChatGPTと著者が二人三脚で執筆！「今の仕事にAIをどう使うか？　考え方一つで「AIの奴隷になるか、AIを奴隷にするか」くらいの大きな違いが出てくる」

技術書の表も裏も知り尽くした人気作家が、読書を血肉にするコツとテクニックを教えます。大好評の「技術書（コンピュータ書）」の読書術を指南する本のオーディオブック版が登場！

ジブンの得意×AIを操るチカラ＝GPT時代の知的生産術ＣｈａｔＧＰＴ時代のＡＩは「ことばで動く」ので、文系人材でも自由自在に操ることができます。

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. 

「ChatGPT」（チャットジーピーティー）は⽂章⽣成AIです。⼈間が⼊⼒した質問に答える形で⽂章を返してくるので「対話型AI」とも呼ばれています。

Data projects are an intrinsic part of an organization's technical ecosystem, but data engineers in many companies continue to work on problems that others have already solved. This hands-on guide shows you how to provide valuable data by focusing on various aspects of data engineering, including data ingestion, data quality, idempotency, and more.

Unlock the full potential of your data with the power of Python. Python for Data Science: A Practical Guide to Data Wrangling, Analysis, and Machine Learning Using Python’s Most Powerful Libraries is your comprehensive roadmap to mastering the tools and techniques that turn raw data into meaningful insights and predictive models.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits.

As data floods into your company, you need to put it to work right away—and SQL is the best tool for the job. With the latest edition of this introductory guide, author Alan Beaulieu helps developers get up to speed with SQL fundamentals for writing database applications, performing administrative tasks, and generating reports. You'll find new chapters on SQL and big data, analytic functions, and working with very large databases.

There's no better time to become a data engineer. And acing the AWS Certified Data Engineer Associate (DEA-C01) exam will help you tackle the demands of modern data engineering and secure your place in the technology-driven future. Authors Sakti Mishra, Dylan Qu, and Anusha Challa equip you with the knowledge and sought-after skills necessary to effectively manage data and excel in your career.

Causal Inference provides a brief and nontechnical introduction to randomized experiments, propensity scores, natural experiments, instrumental variables, sensitivity analysis, and quasi-experimental devices. Ideas are illustrated with examples from medicine, epidemiology, economics and business, the social sciences, and public policy.

When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.

As data continues to grow and become more complex, organizations seek innovative solutions to manage their data effectively. Data mesh is one solution that provides a new approach to managing data in complex organizations. This practical guide offers step-by-step guidance on how to implement data mesh in your organization.

In Fusion Strategy, world-renowned innovation guru Vijay Govindarajan and digital strategy expert Venkat Venkataraman offer a first-of-its-kind playbook that will help industrial companies combine what they do best-create physical products-with what digitals do best-use algorithms and AI to parse expansive, interconnected datasets-to make strategic connections that would otherwise be impossible.

Brought to you by Penguin. THE SUNDAY TIMES BESTSELLER AND A FINANCIAL TIMES, SUNDAY TIMES AND TELEGRAPH BOOK OF THE YEAR 2024 The insider account of the data revolution that has swept through the modern football world written by one of its key architects, Ian Graham. Between 2012 and 2023, Ian...

Excel skills alone are no longer enough. In 2025, the real advantage comes from knowing how to combine Excel with AI. ChatGPT for Excel Beginners shows you how to use ChatGPT as your personal spreadsheet assistant — helping you write formulas, clean messy data, automate tasks, and make better decisions without being an Excel expert.

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very concept of the firm. AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.  

Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. 

This audiobook is a summary of the advice I’ve given to software engineers over the years–and then some more. This audiobook follows the structure of a “typical” career path for a software engineer, from starting out as a fresh-faced software developer, through being a role model senior/lead, all the way to the staff/principle/distinguished level. It summarizes what I’ve learned as a developer and how I’ve approached coaching engineers at different stages of their careers.

In the age of artificial intelligence, machine learning, and data-driven innovation, the quality and quantity of data have become critical to success. Yet real-world data is often incomplete, biased, sensitive, or scarce. Data Generation explores how synthetic, real, and simulated data can be strategically created and used to overcome these limitations—fueling smarter systems, scalable solutions, and more ethical outcomes.

Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career. The first audiobook of its kind, The Kaggle Book assembles in one place the techniques and skills you'll need for success in competitions, data science projects, and beyond.

“One of my favorite books of the year. It completely reshaped how I think about information and how and why I take notes.” —Daniel Pink, bestselling author of Drive A revolutionary approach to enhancing productivity, creating flow, and vastly increasing your ability to capture, remember...

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

We are living in the age of information and there’s no denying it—those who are best at organizing, understanding, and then using data to their advantage will be the ones on top. The skills themselves are simple and easy to learn and will give you a tremendous advantage in the highly competitive marketplace of today’s workforce. The only thing left is for you to give a little commitment and launch yourself into a whole new reality of success.

Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of systems, including relational databases, NoSQL datastores, data...

How to Build an Agent is not a book about experimenting with AI. It is a practical playbook for leaders who need AI systems that work in the real world. Most organisations use generative AI. Few see meaningful business results. This book explains why. Written for executives, senior managers, consultants, and technical leaders, it shows how to move beyond chatbots and prompts to autonomous, outcome-driven AI systems that plan, act, integrate with enterprise software, and deliver measurable ROI.

Drawing on years of work interpreting and explaining data about almost anything, renowned data journalist Kiko Llaneras offers practical tools and shortcuts to help you understand the numbers and make better decisions using a quantitative lens. Through a series of compelling examples, he reveals some of the surprising insights that a data-driven perspective can offer.

Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You’ll explore interesting real-world datasets like Google’s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.